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SUMMARY:Poisson Processes: Applications in Machine Learning - Amar Shah (U
 niversity of Cambridge)
DTSTART:20120524T130000Z
DTEND:20120524T143000Z
UID:TALK37510@talks.cam.ac.uk
CONTACT:Konstantina Palla
DESCRIPTION:Poisson processes form an incredibly powerful class of distrib
 utions with elegant modelling properties. \nWhilst thoroughly studied in t
 he applied probability community over the last few decades\, they have yet
  \nto stir up a big fuss in the machine learning community. Nonetheless\, 
 there have been a collection of fairly \nrecent papers which apply them in
  a variety of interesting ways.\n\nIn this talk I aim to outline some basi
 c definitions and properties of Poisson processes and give a flavour of \n
 how they can be used\, incorporating some Bayesian nonparametric machinery
 . To benefit most from the talk\, \nit’d be helpful to familiarise yours
 elf with the definition and basic properties of a Poisson process. \n\n
LOCATION:Engineering Department\, CBL Room 438
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